Sameness Index · 5 sites compared

Your page scores 46 out of 100 for sameness against the 4 competitors you named.

https://www.growthbook.io/

01

Your verdict

46
Sameness · vs 4 named
How is this calculated?

Your page is half shared.

About half of what your page says, Eppo (now Datadog Experiments) also says. You're less same than 5 of the 8 Digital analytics sites scored (category avg 52).

Benchmarked against Digital analytics (the category you chose).
Sameness Index on a 0 to 100 scale, from distinctive at 0 to interchangeable at 100. This page scores 46. Statsig scores 71. Eppo (now Datadog Experiments) scores 57. Kameleoon scores 63. LaunchDarkly scores 50. The category avg is 52.

Each named site is scored the same way, against the other 4 in this set, so its tick means the same as your marker. The dashed line is the frozen benchmark average.

  1. Less same than average

    The average Digital analytics category leader scores 52; you scored 46.

    You are 6 points less same than the average Digital analytics category leader.

  2. Closest overlap: Eppo (now Datadog Experiments)

    Of the 4 sites you named, Eppo (now Datadog Experiments) echoes the most of what your page says. Scored the same way against the rest of the set, Eppo (now Datadog Experiments) sits at 57.

    Eppo (now Datadog Experiments) is the competitor you sound most like.

  3. Room to own more

    8% of your claim space is ownable: unique, relevant, and hard to copy. 2 of those claims sit in body copy, where few readers reach them.

    8% is ownable, and 2 buried opportunities could help you stand out more.

Do this first

Three changes worth testing first.

Chosen by rule from the comparison with Statsig, Eppo (now Datadog Experiments), Kameleoon and LaunchDarkly: the shared claim taking your most prominent space, then the claims only you make that sit too low on the page to be read. Each one links to its claim card.

  1. Build smarter. Ship safely. Grow at the speed of AI.

    Statsig, Eppo (now Datadog Experiments), Kameleoon and LaunchDarkly all say it too. Buyers may still need it, but shared ground cannot carry your hero — move it lower and give that space to something only you can say.

    Table stakes
    Most of the set says this too.
  2. Define metrics in SQL on your data warehouse

    Nobody in the set says this. It sits in body copy, where few readers reach it — worth testing higher up the page; only buyers can tell you whether it lands.

    Surface
    Yours alone. Test it higher up.
  3. Open source and transparent

    A claim that is yours alone, filed in body copy. Try it where it will be read before the shared claims are, and let buyers tell you if it moves them.

    Surface
    Yours alone. Test it higher up.

Try these changes, then test them with real buyers.

This measures overlap. Whether buyers notice is a different question, and only they can answer it.

02

What you can own

Claims only you make, that buyers weigh, and that competitors can’t easily copy.

8% of your page’s claim space is yours to keep.

8%Yours to keep11%Unique but weak81%A competitor says it too
Why this is not 100 minus the Sameness Index

The index is a weighted composite across six categories, including page structure and visuals. This bar is measured on your claims alone, weighted by where each one sits on the page. Different denominators, so the two never add to 100 and are not meant to.

Already leading with · 1

  1. Available as cloud or self-hosted/on-prem

    GrowthBook Cloud: Instant updates, low maintenance, and warehouse-native

Buried in body copy · 2

  1. Define metrics in SQL on your warehouse

    Define metrics in SQL on your data warehouse

  2. Open source and transparent codebase

    Open source and transparent

03

Where you blend in

Territory you spend prominent space on that the set also occupies. Not every line is one to delete — the question is whether it has earned the space, or whether something only you can say should be there instead.

  • Commodity · 100%Table stakesHero
    safe rollouts with guardrails and rollbacks
    • Build smarter. Ship safely. Grow at the speed of AI.
    • auto-rollbacks and ramp schedules with guardrails

    You say this 2 different ways.

    Statsig, Eppo (now Datadog Experiments), Kameleoon and LaunchDarkly all cover this territory. Buyers may need to hear it, but in your hero it spends the first impression on shared ground.

    They say
    • Statsigprotect trust and optimize at the speed of AI
    • Eppo (now Datadog Experiments)Make every deployment into an automated safe rollout
    • KameleoonUse flags to manage releases, target users progressively, and control rollout based on real-time performance data
    • LaunchDarklyOwn what ships—down to the last detail.
  • Commodity · 100%Table stakesSection
    customer results and testimonials as proof
    • +30% account creation

    Common ground with Statsig, Eppo (now Datadog Experiments), Kameleoon and LaunchDarkly. Say it if buyers need it — lower on the page, where it is not the thing they read first.

    They say
    • StatsigBrex's data teams achieved a +50% time efficiency gain by consolidating their product data, experimentation, and analytics in one platform
    • Eppo (now Datadog Experiments)After switching to Eppo, our Product Managers are spending 50% less time making dashboards and debugging issues
    • KameleoonWith Prompt-based Experimentation we went from running a few experiments per quarter to launching ideas in real time (customer quote)
    • LaunchDarklySavage X Fenty keeps shoppers engaged with rapid, reliable experiments.
  • Commodity · 100%Table stakesSection
    one platform combining flags, experiments and analytics
    • One platform for your team and your agents

    Statsig, Eppo (now Datadog Experiments), Kameleoon and LaunchDarkly make the same claim. It cannot set you apart, so it should not carry the section.

    They say
    • StatsigStatsig gives your team 5+ products in a single platform
    • Eppo (now Datadog Experiments)Use one platform for everything from simple feature gates to AI personalization
    • KameleoonBuild, test, and roll out—all in one place
    • LaunchDarklyExperiment continuously.
  • Commodity · 100%Table stakesSection
    turns product data into actionable insights
    • Turn data into insights for growth

    A buyer comparing tabs sees this on Statsig, Eppo (now Datadog Experiments), Kameleoon and LaunchDarkly. Yours earns nothing by repeating it up top; it can live lower down.

    They say
    • StatsigTurn action into insights and insights into action
    • Eppo (now Datadog Experiments)Run experiments on your company's core business metrics, not on vanity metrics
    • KameleoonLearn what works and what to do next
    • LaunchDarklyKnow exactly what changed—and why it matters.
  • Commodity · 75%Table stakesSection
    AI assists analysis and test creation
    • Ask our AI Analyst or explore your data with your agents

    Eppo (now Datadog Experiments), Kameleoon and LaunchDarkly got here first as far as a buyer can tell. Keep the fact for readers who need it; move the position to a claim only your page can make.

    They say
    • Eppo (now Datadog Experiments)Plan roadmaps that drive impact and measure their performance with Experiment Forecasts
    • KameleoonAsk AI to identify ideas worth testing
    • LaunchDarklyOptimize AI performance and cost.
  • Commodity · 75%Table stakesSection
    named customers and customer counts as proof
    • Dropbox uses GrowthBook to safely drive AI product development
    • Trusted by 3,000+ companies worldwide

    You say this 2 different ways.

    Shared with Statsig, Eppo (now Datadog Experiments) and Kameleoon, 75% of the set. True of you, true of them — which is exactly why it will not decide anything.

    They say
    • StatsigLoved by customers at every stage of growth
    • Eppo (now Datadog Experiments)Companies like Twitch, DraftKings, and Perplexity use Eppo to power experimentation for every team
    • KameleoonOver +1,000 brands experimenting with Kameleoon
  • Commodity · 75%Table stakesSection
    rigorous experimentation with advanced statistics
    • built for your teams and agents to run rigorous tests at scale and learn faster
    • More experiments

    You say this 2 different ways.

    Nothing wrong with the claim; Statsig, Eppo (now Datadog Experiments) and Kameleoon just make it as well. Treat it as the price of entry and spend the prominent space elsewhere.

    They say
    • StatsigBuild a complete set of product metrics, iterate with flags and experiments, then analyze the results with a world-class stats engine and advanced product…
    • Eppo (now Datadog Experiments)Automate experimentation analysis, deep dives, and diagnostics with trusted statistical methods
    • KameleoonConfidently scale your experimentation program
  • Contested · 50%SharpenSection
    costs less than alternatives
    • 1/2 The cost of other solutions

    Statsig and Eppo (now Datadog Experiments) are on this territory too (50% of the set). It narrows the field without winning it — make it specific enough that it cannot be said of them.

    They say
    • Statsigshockingly affordable
    • Eppo (now Datadog Experiments)Eppo's pipelines are optimized to keep your data warehouse bills down
  • Contested · 50%SharpenSection
    scale proven by usage volume metrics
    • 3 billion feature evaluations daily

    Shared with Statsig and Eppo (now Datadog Experiments). Sharpen it to the thing only you do here, or it reads as a claim any of you could make.

    They say
    • Statsig1+ Trillion events processed per day
    • Eppo (now Datadog Experiments)Powering billions of daily assignments
  • Contested · 25%KeepHero
    warehouse-native metrics defined in SQL
    • The warehouse-native platform used by modern product teams for experimentation, feature flags, and product analytics

    Eppo (now Datadog Experiments) say what they are and who they are for, as every page in a category must. Keep it — it is orientation, not differentiation.

    They say
    • Eppo (now Datadog Experiments)Ensure trust in data with zero-copy, warehouse-native architecture
  • Contested · 25%SharpenSection
    developer-friendly, flexible and open
    • Built by engineers for engineers to adapt to any workflow or tech stack

    Contested ground: LaunchDarkly claim it as well. The version that wins names a mechanism, a number or a scope that theirs cannot match.

    They say
    • LaunchDarklyBuilt for developers and their agents.
04

Claim-by-claim evidence

Every claim on your page (24)
What the columns mean
Claim
The grouped claim, then your exact line beneath it.
Type
What kind of claim it is: category, segment, outcome, capability, quality or proof.
Placement
Where it sits on your page: hero, section or body copy. Hero claims weigh most in the index.
Same claim
Share of the competitors making this exact claim. Drives ownership and ownable share.
Same territory
Share of the competitors with any claim in the same buyer-facing territory. This is what the index is scored on.
Sayability
Whether a competitor could truthfully make the same claim: anyone could, copyable with effort, or hard to copy.
Relevant
Whether buyers decide on this. A unique claim nobody buys on is not ownable.
Ownership
Commodity: 60% or more of the set says it. Contested: 20–59%. Unique: under 20%, owned when it is also hard to copy.

Tap a column to sort by it; tap again to reverse. Sorted by Same claim, highest first.

  • Customer increased experiment velocity and business metrics
    +30% account creation
    proofSectionsame claim 75%same territory 100%Anyone could say it
    Commodity
    Also on Statsig, Kameleoon, LaunchDarkly
  • One platform combining flags, experiments and analytics
    One platform for your team and your agents
    capabilitySectionsame claim 75%same territory 100%Copyable with effort
    Commodity
    Also on Statsig, Eppo (now Datadog Experiments), Kameleoon
  • Ship AI-generated code safely and fast
    Build smarter. Ship safely. Grow at the speed of AI.
    outcomeHerosame claim 50%same territory 100%Anyone could say it
    Contested
    Also on Statsig, LaunchDarkly
  • Automatic guardrails, rollbacks and safe rollouts
    auto-rollbacks and ramp schedules with guardrails
    capabilitySectionsame claim 50%same territory 100%Copyable with effort
    Contested
    Also on Eppo (now Datadog Experiments), LaunchDarkly
  • Costs less than competing solutions
    1/2 The cost of other solutions
    outcomeSectionsame claim 50%same territory 50%Anyone could say it
    Contested
    Also on Statsig, Eppo (now Datadog Experiments)
  • Massive daily flag evaluation volume
    3 billion feature evaluations daily
    proofSectionsame claim 50%same territory 50%Hard to copy
    Contested
    Also on Statsig, Eppo (now Datadog Experiments)
  • Run rigorous experiments at scale with advanced statistics
    built for your teams and agents to run rigorous tests at scale and learn faster
    capabilitySectionsame claim 50%same territory 75%Copyable with effort
    Contested
    Also on Statsig, Eppo (now Datadog Experiments)
  • Scale to thousands of experiments per year
    More experiments
    outcomeSectionsame claim 50%same territory 75%Anyone could say it
    Contested
    Also on Statsig, Kameleoon
  • Trusted by thousands of companies
    Trusted by 3,000+ companies worldwide
    proofSectionsame claim 50%same territory 75%Anyone could say itnot a buying criterion
    Contested
    Also on Statsig, Kameleoon
  • Governance of metric definitions and workflows org-wide
    Set guardrails for consistency & scale
    capabilityBodysame claim 50%same territory 100%Copyable with effort
    Contested
    Also on Eppo (now Datadog Experiments), Kameleoon
  • Lightweight SDKs, easy integration, low latency
    Easy to integrate with ultra lightweight SDKs
    qualityBodysame claim 50%same territory 75%Copyable with effort
    Contested
    Also on Statsig, Kameleoon
  • Non-technical users self-serve analysis without data team
    Enable self-serve data explorations
    capabilityBodysame claim 50%same territory 75%Copyable with effort
    Contested
    Also on Eppo (now Datadog Experiments), Kameleoon
  • Warehouse-native architecture for experiment data
    The warehouse-native platform used by modern product teams for experimentation, feature flags, and product analytics
    categoryHerosame claim 25%same territory 25%Copyable with effort
    Contested
    Also on Eppo (now Datadog Experiments)
  • AI assistant answers analysis questions
    Ask our AI Analyst or explore your data with your agents
    capabilitySectionsame claim 25%same territory 75%Anyone could say itnot a buying criterion
    Contested
    Also on Kameleoon
  • Built by engineers, developer-friendly and flexible
    Built by engineers for engineers to adapt to any workflow or tech stack
    qualitySectionsame claim 25%same territory 25%Anyone could say it
    Contested
    Also on LaunchDarkly
  • Named enterprise customers use the product
    Dropbox uses GrowthBook to safely drive AI product development
    proofSectionsame claim 25%same territory 75%Anyone could say itnot a buying criterion
    Contested
    Also on Eppo (now Datadog Experiments)
  • Turn product data into growth insights
    Turn data into insights for growth
    outcomeSectionsame claim 25%same territory 100%Anyone could say it
    Contested
    Also on Statsig
  • Agent-accessible via MCP server and APIs
    MCP Server and REST API for any AI agent
    capabilityBodysame claim 25%same territory 75%Copyable with effort
    Contested
    Also on LaunchDarkly
  • Faster results and bigger impactgrouping uncertain
    used by modern product teams
    segmentHerosame claim 0%same territory 0%Anyone could say itnot a buying criterion
    Unique for now
  • Available as cloud or self-hosted/on-prem
    GrowthBook Cloud: Instant updates, low maintenance, and warehouse-native
    capabilitySectionsame claim 0%same territory 0%Copyable with effort
    Unique and owned
  • Automatically instrument new features with flags
    Automatically add flags to new features
    capabilityBodysame claim 0%same territory 0%Copyable with effortnot a buying criterion
    Unique and owned
  • Define metrics in SQL on your warehouse
    Define metrics in SQL on your data warehouse
    capabilityBodysame claim 0%same territory 25%Copyable with effort
    Unique and owned
  • Open source and transparent codebase
    Open source and transparent
    qualityBodysame claim 0%same territory 25%Copyable with effort
    Unique and owned
  • Real-time debugging and developer tooling
    Real-time debugging and more dev tools
    capabilityBodysame claim 0%same territory 0%Anyone could say itnot a buying criterion
    Unique for now
05

How this was calculated

Sameness measures how much your claims overlap with the sites compared. It does not measure message quality or whether buyers prefer you.

AI-analyzed: an AI read each page on its own and grouped the claims that say the same thing. No score here was written by a model — every number is computed from those groupings in our own code, with the weights below.

How the score is built
The six category scores, their weights, and what a high score in each one means
CategoryWeightYoursWhat a high score means
Messaging
Category framing, who it is for, and the outcome promised
30%54The most expensive kind of sameness. A buyer cannot tell what job you do that the others do not.
Claims
Attribute and benefit claims — speed, ease, quality, ROI
30%35Every shared claim is a line already read on another tab. Cut the ones nobody owns and spend the space on something they cannot.
Features
Capabilities and functions the page lists
15%63Expected in a mature category, and the least alarming of the six. Feature parity is normal; leading with it is the mistake.
Proof
The kinds of evidence offered: customer logos, numbers, testimonials, case studies, badges
10%36Same kinds of proof as everyone means the proof stops working as proof. It is scored on the kind of evidence, not on which customers are named.
Structure
Section order, navigation, CTA language and placement
10%35The generic SaaS template — hero, logos, three-feature grid, testimonial, CTA. Familiar is not the same as memorable.
Visual
Palette family, imagery style, layout patterns
5%61Weighted lowest on purpose: buyers rarely decide on this. Worth knowing, rarely worth fixing first.

Each site was read on its own first, with no knowledge of the others, so your page gets no benefit of the doubt a competitor’s does not. A category nothing could be measured for drops out and the rest are re-weighted, rather than counted as zero.

What we compared (5 pages read)
Your page
GrowthBook
growthbook.io
Competitor
Statsig
statsig.com
Competitor
Eppo (now Datadog Experiments)
geteppo.com
Competitor
Kameleoon
kameleoon.com
Competitor
LaunchDarkly
launchdarkly.com
What it cannot tell you

The index can find where two pages converge. It cannot say whether a buyer would notice, or which of your reasons to buy actually land. A single check also moves several points between runs, so read the band and the ranking, not the last digit.

Your highest-impact changes

  1. 1
    Table stakesYour hero copy says “Build smarter. Ship safely. Grow at the speed of AI.”.

    Statsig, Eppo (now Datadog Experiments), Kameleoon and LaunchDarkly all say it too. Buyers may still need it, but shared ground cannot carry your hero — move it lower and give that space to something only you can say.

  2. 2
    Table stakesYour section copy says “auto-rollbacks and ramp schedules with guardrails”.

    Keep the fact, lose the position: statsig, Eppo (now Datadog Experiments), Kameleoon and LaunchDarkly all say it too, and your section is spending its first impression on the same territory as theirs.

  3. 3
    Table stakesYour section copy says “+30% account creation”.

    This is the set's common ground — Statsig, Eppo (now Datadog Experiments), Kameleoon and LaunchDarkly all say it too. It will not set you apart wherever it sits, and in the section it costs you the one place a distinctive claim would be read.

  4. 4
    Table stakesYour section copy says “One platform for your team and your agents”.

    A buyer with three tabs open reads a version of this on every one of them. Say it further down for the readers who need it; the section should carry a claim they will only find here.

  5. 5
    Table stakesYour section copy says “Turn data into insights for growth”.

    True of you and true of them: Statsig, Eppo (now Datadog Experiments), Kameleoon and LaunchDarkly all say it too. That is why it decides nothing, and why the section is the wrong place to spend it.

  6. 6
    Table stakesYour section copy says “built for your teams and agents to run rigorous tests at scale and learn faster”.

    In the section: Statsig, Eppo (now Datadog Experiments) and Kameleoon say it too (75% of the set). Buyers may still need it, but shared ground cannot carry your section — move it lower and give that space to something only you can say.

  7. 7
    Table stakesYour section copy says “More experiments”.

    In the section: True of you and true of them: Statsig, Eppo (now Datadog Experiments) and Kameleoon say it too (75% of the set). That is why it decides nothing, and why the section is the wrong place to spend it.

  8. 8
    Table stakesYour section copy says “Trusted by 3,000+ companies worldwide”.

    In the section: Keep the fact, lose the position: statsig, Eppo (now Datadog Experiments) and Kameleoon say it too (75% of the set), and your section is spending its first impression on the same territory as theirs.

  9. 9
    Surface“Define metrics in SQL on your data warehouse” is yours alone, and buyers weigh it.

    Nobody in the set says this. It sits in body copy, where few readers reach it — worth testing higher up the page; only buyers can tell you whether it lands.

  10. 10
    Surface“Open source and transparent” is yours alone, and buyers weigh it.

    A claim that is yours alone, filed in body copy. Try it where it will be read before the shared claims are, and let buyers tell you if it moves them.

The only way to know if it matters.

This report can tell you where your messaging overlaps. It cannot tell you whether a buyer would care, or which of your reasons to buy actually land. Put the page in front of real B2B buyers in your target market and ask them.

Test it with real buyers
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